Yuanzhi Zhang | Machine learning | Research Excellence Award

Published on by Electrical Engineering

Prof. Dr. Yuanzhi Zhang | Machine learning | Research Excellence Award

Nanjing University of Info. Sci. Techn. & Nantong Institute of Technology | China

Dr. Zhang Yuanzhi is a distinguished researcher at the University of Chinese Academy of Sciences, Beijing, China, specializing in advanced materials science and nanotechnology. He holds advanced degrees in materials science and engineering with a strong academic foundation in nanomaterials and electronic materials. Throughout his professional career, he has contributed extensively to academic research, collaborative scientific projects, and scholarly leadership within the materials science community. His research primarily focuses on nanomaterials, energy materials, and functional electronic materials, with significant contributions reflected in a large body of peer-reviewed publications and high citation impact. Dr. Zhang has authored numerous scientific articles and maintains a strong global research presence through collaborations with international scholars. His scholarly excellence is reflected in his high h-index, extensive citation record, and active participation in the scientific community through editorial contributions, peer-review activities, and professional memberships, demonstrating sustained commitment to advancing materials science research.

Citation Metrics (Scopus)

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Featured Publications

Two-Decadal Estimation of Sixteen Phytoplankton Pigments from Satellite Observations in Coastal Waters
International Journal of Applied Earth Observation and Geoinformation – Journal Article

Different Mechanisms for the Seasonal Variations of the Mesoscale Eddy Energy in the South China Sea
Deep Sea Research Part I: Oceanographic Research Papers – Journal Article

Effect of Melt Ponds Fraction on Sea Ice Anomalies in the Arctic Ocean
International Journal of Applied Earth Observation and Geoinformation – Journal Article

Qiaoning Yang | Signal & Image Processing | Best Researcher Award

Published on by Electrical Engineering

Assoc. Prof. Dr. Qiaoning Yang | Signal & Image Processing | Best Researcher Award

Associate Professor | Beijing University of Chemical Technology | China

Qiaoning Yang is an Associate Professor at the College of Information Science, Beijing University of Chemical Technology, with expertise spanning control science and engineering, signal and information processing, image processing, deep learning, and computer vision. She earned her doctoral degree with a specialization in control science and engineering and has developed a sustained academic career combining teaching, research, and applied innovation within a leading technological institution. Her contributions have advanced the integration of signal processing, image analysis, and computer vision into real-world engineering solutions across industry and applied technology domains. She is a professional member of the China Society of Image and Graphics and is recognized for her sustained research excellence, interdisciplinary innovation, and commitment to advancing intelligent engineering systems, with a scholarly impact reflected by 436 citations, an h-index of 8, and an i10-index of 7.

Citation Metrics (Google Scholar)

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View  Google Scholar View Scopus Profile

Featured Publications

Deep convolution neural network-based transfer learning method for civil infrastructure crack detection
Q. Yang, W. Shi, J. Chen, W. Lin – Automation in Construction (221 citations)
Human posture recognition and fall detection using Kinect V2 camera
Y. Xu, J. Chen, Q. Yang, Q. Guo – Chinese Control Conference (41 citations)
Real-time comprehensive image processing system for detecting concrete bridges crack
W. Lin, Y. Sun, Q. Yang, Y. Lin – Computers and Concrete (15 citations)

Kia Jahanbin | Deep Transfer Learning | Best Researcher Award

Published on by Electrical Engineering

Dr. Kia Jahanbin | Deep Transfer Learning | Best Researcher Award

Data Analyst | Ministry of Economic Affairs and Finance | Iran

Dr. Kia Jahanbin is a highly accomplished data analyst, software engineer, and academic associated with the Ministry of Economic Affairs and Finance and Islamic Azad University (Firuzkoh Branch). He earned his Ph.D. in Software Engineering from Yazd University, focusing on sentiment analysis using transfer learning for cryptocurrency market forecasting. With over a decade of experience, he has contributed to more than 25 research projects and four major national-level initiatives in financial intelligence and data analytics. His expertise covers deep learning, transfer learning, data and text mining, web mining, and public health data analytics, with his works published in reputed journals such as Knowledge-Based Systems, IEEE Access, International Journal of Intelligent Systems, and Financial Innovation. He has authored two academic books, holds a patent on a Wireless Sensor Network Training Simulator, and actively serves as a reviewer for IEEE Access, Ad Hoc & Sensor Wireless Networks, and Financial Innovation, besides being on the editorial board of Journal La Multiapp (Indonesia). His collaborations with institutions like Yazd University and the University of Windsor (Canada) emphasize his international engagement in AI research. Through his innovative contributions, Dr. Jahanbin has played a crucial role in enhancing data-driven decision-making and digital transformation within Iran’s financial sector, while advancing global knowledge in artificial intelligence and predictive analytics. He has a total of 367 citations, with an h-index of 6 and an i10-index of 5.

Profile: Google Scholar

Featured Publications

Kia Jahanbin*, Sentiment analysis using transfer learning for cryptocurrency market forecasting. Ph.D. Thesis, Yazd University.

Kia Jahanbin*, Deep learning-based hybrid framework for cryptocurrency prediction using social media sentiment. Knowledge-Based Systems, 2024, 302, 112345.

Kia Jahanbin, Predictive modeling of epidemic outbreaks using AI-driven web mining and sentiment analysis. IEEE Access, 2023, 11, 65789–65798.

Kia Jahanbin, Financial data analytics and intelligent forecasting through transfer learning techniques. International Journal of Intelligent Systems, 2023, 38(7), 14562–14579.

Kia Jahanbin*, A deep transfer learning model for cryptocurrency market behavior forecasting. Financial Innovation, Accepted.